JP3412013B2 - Obstacle collision prevention support system - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an obstacle collision for the purpose of improving safety by detecting the information of an obstacle or the like with a visible image sensor and providing the information to the driver in a curve section where accidents frequently occur. This is related to the prevention support system, and in particular, when a device failure or a functional failure such as a decrease in sensor detection performance due to bad weather occurs, the sensor performance deterioration or device failure is diagnosed and the system operates normally. The present invention relates to an obstacle collision prevention support system that ensures reliability and safety of information provision by notifying the driver that there is no such problem.

[0002]

2. Description of the Related Art AHS (Advanced Cruise-Assist Syste
m) aims to improve safety and efficiency. Among them, AHS aimed at improving safety includes smart cars (intelligent cars) and smart ways (intelligent roads). By collaboratively exchanging information such as obstacles and crossing vehicles, which were not possible in the past, in real time, information is provided for delays in driver discovery, warnings are given for incorrect judgments, and operational support for operational errors is provided. Is a system that realizes safe driving and reduces accidents. Until now, the selection of services that should be prioritized based on statistical analysis of traffic accidents has been considered, and among them, the need for obstacle collision prevention support in curved sections has been clarified.

In an obstacle collision prevention support system, a stopped vehicle, a low speed vehicle, or a reverse running vehicle existing in a curve section using a camera installed on a roadside pole and an image captured by the camera in a curve section where accidents frequently occur. An obstacle detection means including an image processing device for detecting an obstacle such as an oncoming vehicle and an oncoming vehicle,
Obstacle information creating means including an information processing device that creates provided information based on the output of the obstacle detecting means, an information board installed on the roadside, or a road-to-vehicle communication device to provide information to a driver of a passing vehicle. This system is composed of obstacle information providing means and is intended to support safe driving by providing information to drivers and warnings.

However, since the visible image sensor, which is mainly used as the obstacle detecting means, detects the obstacle by the image processing device using the image picked up by the camera, the detection performance is deteriorated when the visibility deteriorates due to bad weather or the like. It will be significantly reduced.

FIG. 13 shows a conventional image processing apparatus described in Technical Research Report PRMU97-6 of the Institute of Electronics, Information and Communication Engineers,
A camera 11 that captures an image, and an input image storage unit 2 that stores the image captured by the camera 11 as digital data
1. Initial detection means 50 for initial detection of an object targeting a partial area in an input image, tracking means 51 for tracking an object,
This is an apparatus including an output unit 52 that outputs a processing result.

Further, FIG. 14 is a diagram of Japanese Patent Laid-Open No. 63-188741.
In the conventional visibility measuring device described in Japanese Patent Publication No. JP-A-2003-264, a light-dark detection device 200 for detecting the light-dark contrast of a judgment mark, and a light-dark contrast when the judgment mark is viewed from a close distance and a light-dark contrast detected by the light-dark detection device 200. The image processing apparatus 201 is provided to obtain the visibility based on the image processing apparatus 201. The image processing device 201 is composed of a plurality of blocks, and an A / D converter 300 for digitally converting the image information output as an analog signal by the brightness detection device, and a digital signal converted by the A / D converter 300. It has an image memory 301 for storing image data, a CPU 302 for controlling the processing of the image processing apparatus 201, a memory 303 connected to the CPU 302, and an output unit 304 for outputting the processing result in the CPU 302.

The operation of the conventional image processing apparatus will be described. First, an image captured by the camera 11 is digitally converted by the input image storage means 21 and stored as an input screen.

Next, the initial detection means 50 performs the initial detection of the object on a predesignated area in the input image. First, the target area is differentiated in the vertical direction to emphasize the bright and dark patterns in the horizontal direction, and this is projected and added in the vertical direction to create an analysis waveform. A threshold value is applied to this analysis waveform to find the rising and falling edges of the waveform, and the area sandwiched between the two is set as the horizontal position of the object. Further, a horizontal light-dark pattern is projected in the horizontal direction on the area within the object horizontal position, and the object vertical position is determined with the position where the projected value becomes maximum. The image of the object area and the position coordinates obtained here are output to the tracking means 51 as a result of the initial detection.

Next, the tracking means 51 traces the detected object by calculating the degree of similarity by light and shade pattern matching using the image of the object area detected by the initial detection means in the past as a template.

Next, the operation of the conventional visibility measuring device shown in FIG. 14 will be described. The light-and-darkness detection device 200 captures an image including a determination mark painted in black and white, and outputs the image data as an analog signal. At this time, the determination mark is installed at a position separated from the brightness detection device 200 by a distance R.

In the image processing device 201, first, the image data sent from the brightness detection device 200 is processed by the A / D converter 3.
At 00, it is converted into a digital signal and stored in the image memory 301. Next, the CPU 302 reads the brightness value Bt of the part painted in black and the brightness value Bb of the part painted white for the judgment marker area in the image, and obtains the light-dark contrast Cd of the judgment marker from the following equation.

Cd = | Bt-Bd | / Bb

Next, the CPU 302 determines the visibility V based on the light-dark contrast Cd of the judgment mark at the distance R and the light-dark contrast Co of the judgment mark when viewed from close up.
Is calculated by the following equation and output to the output unit 304.
This visibility V indicates a visible distance.

[0014] V = R × [In (E) / In (Cd / Co)] However, E is a constant.

[0015]

As described above, the image processing apparatus used in the conventional obstacle collision prevention support system is as follows.
Obstacles are detected without considering environmental conditions such as rain and fog that affect the field of view of the camera. Therefore, when obstacles cannot be detected, the obstacles that should actually be detected are not within the field of view of the camera. It is impossible to judge whether the visibility cannot be detected even if there is an obstacle or the like because the visibility is deteriorated depending on the environmental condition.

In the obstacle collision prevention support system,
If an obstacle is present but cannot be detected, the driver may think that there is no obstacle, which increases the risk. Therefore,
There is a problem in that it is necessary to provide the system with an important function to notify the driver that the system is not operating normally by making it possible to self-diagnose a device failure or sensor performance deterioration. To this end, the system itself must be able to detect device failures and diagnose sensor performance degradation, and if a device failure or performance degradation is diagnosed, notify the driver that the system is not operating. . In order to solve this problem, a method of using a conventional visibility measuring device in combination is also conceivable, but the conventional visibility measuring device, as described above, seeks general good visibility as the visibility. The failure cannot be determined, and the environmental condition cannot be determined in the sense that the environmental condition is such that an obstacle can be detected.

[0017]

SUMMARY OF THE INVENTION The present invention solves the problems of the conventional system as described above, and the detection performance of the visible image sensor deteriorates with the detection of equipment failure and the occurrence of rain, fog, etc. Automatically notifies the driver that the system is not operating when the device failure is detected as a result of the self-diagnosis or when the deterioration of the detection performance is judged by the self-diagnosis. This is an obstacle collision prevention support system.

[0018]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below based on examples with reference to the drawings.

[0019]

Embodiment 1 FIG. 1 is a schematic equipment layout diagram in one embodiment to which the present invention is applied. In FIG. 1, equipment is arranged in a curve section 100 in which accidents frequently occur, and a wall 101 or the like that blocks the line of sight of the curve section, and a driver or the like of a traveling vehicle entering the curve section can see through the wall or the like 101. AHS that can not be stopped and has on-vehicle device 102 and on-vehicle device 103, and is equipped with vehicle-mounted device to obtain information in real time by road-to-vehicle communication
Non-AHS vehicle 1 that obtains information from vehicle 104 and information board 6
05, Paul 2, cameras 11, 12, camera 12 to 1
The size of one side provided at a height of 3.8 m or more of the pole 2 with the camera 11 within the field of view of 00 m is 50 c
A mark plate 3 of m or more, a roadside processing device 4 including an image processing device, an information processing device, a road-vehicle communication interface, and the like, a beacon antenna 5 of the road-vehicle communication device, and the like are included.

FIG. 2 is a schematic configuration diagram of the first embodiment, in which the brightness of the mark area is extracted as an observation value from the image of the camera that captures the mark plate to obtain an evaluation value, and it is obtained when the visibility is the most clear in the past. By comparing the evaluation value output by the environmental condition detecting unit 23 and the environmental condition detecting unit 23, which detects a change in the environmental condition affecting the field of view of the camera, such as rain and fog, by normalizing the evaluated value with the vehicle detection reference data, Self-diagnosis means 24 that determines and outputs the detection capability of the obstacle detection means based on a predetermined threshold, device failure detection means 25 that detects a failure of a camera, processing results of obstacle detection means, self-diagnosis means, and equipment failure detection means. Output processing result output means 26, obstacle information creation means, device failure detection means, and self-diagnosis means output information creation means 31 for outputting as an editing section, information board installed on the roadside Rui is composed of system operation notification means 41 for notifying the obstacle information providing unit and system operation abnormality that provide obstacle information to the passing vehicle driver by road-vehicle communication device.

Next, the operation of the system of the first embodiment will be described with reference to FIGS.
This will be described with reference to FIG. FIG. 3 is a processing flow chart of the present invention. FIG. 4 is a diagram for explaining the size of the mark plate and the distribution of brightness. 5 to 8 show that the mark plate shown in FIG. 4 is installed 40 m, 60 m, 80 m, and 100 m in front of the camera, and the evaluation value of the environmental condition detected for each change of the environmental condition and the detection position of the traveling vehicle are obtained by an experiment. The vehicle detection reference data (1) to (4) are shown. Further, FIG. 9 is a diagram in which a correlation coefficient between the evaluation values of the vehicle detection reference data (1) to (4) and the vehicle detection position is obtained, and FIG. 10 is obtained by the device operation information creating means and the obstacle information creating means. It is a figure explaining the data structure to output.

First, the presence or absence of a device failure for detecting a failure of a camera or the like is detected (step T2). For device failure detection, for example, an image output abnormality or a camera failure can be detected by monitoring an image synchronization signal.

The camera 12 captures an image including the mark plate 3 (step T1), and the input image storing means 21 stores the image in the camera 1.
The image captured in 2 is stored as digital data (step T3). As shown in FIG. 4, the mark plate 3 of the image stored in the input image storing means 21 is colored white in the central part and black in the peripheral part, and the size of the mark plate is in front of the camera. In order to obtain a stable image even when installed at 80 m to 100 m, one side is 50 so that the number of pixels in the mark plate area of the image is about 10 pixels or more.
It is necessary to set it to cm or more. Input image storage means 2
The brightness is obtained as an observation value from the mark plate area in the image stored in 1. For example, as shown in FIG. 4, a horizontal observation line is set at the center of a mark plate image having a width of n pixels, and the brightness of each image in the horizontal direction is obtained. FIG. 4 shows the difference in the distribution regarding the brightness of the image capturing this mark at the time of normal and bad weather. As shown in 32 in normal time and in 33 in bad weather, in the brightness distribution, the gradient of the brightness value at the boundary between black and white changes, and this gradient represents the environmental condition.

Next, the environmental condition detecting means 23 calculates an environmental condition evaluation value (step T8). In this step, for example, the environmental condition evaluation value S is calculated for the target region from the brightness value output from the observed value by the following formula. Here, Pj is the luminance value at the pixel position j between the observation lines −L and L.

[Equation 1]

Next, the environmental condition detecting means 23 sets the environmental condition evaluation value to a reference evaluation value obtained in the past during fine weather (step T10) and normalizes it (step T9). The normalized evaluation value D to be normalized is obtained by the following equation after being normalized by the reference evaluation value Smax in fine weather. D = S / Smax

Next, the self-diagnosis means 24 collates the normalized evaluation value output from the environmental condition detection means 23 with the vehicle detection reference data, judges the detection capability of the obstacle detection means 22 by a predetermined threshold value, and outputs the judgment result. Yes (step T11).
Here, the vehicle detection reference data is set in advance as follows.

A plurality of mark plates are placed at a distance R in front of the camera.
Different position, for example, the distance R from the camera is 40 m,
The environmental condition detected by the environmental condition detecting unit 23 and the obstacle detecting unit 22 which are installed at positions 60 m, 80 m, and 100 m ahead and detect the environmental condition at each of a plurality of mark plate installation positions, in response to changes in the environmental condition in the past. The evaluation value of and the position where the traveling vehicle can be detected are obtained.

5 to 8 show a mark plate having a side of 50 cm and a distance R from the camera of 40 m, 60 m, 80 m, 1
When installed at a position in front of 00m, the reference data (1) to (4) of the vehicle detection distance and the normalized evaluation value D are shown. The reference data (1) to (4) are data obtained at an experimental facility capable of generating and setting a rain fog environment under arbitrary conditions. Further, based on the result, FIG. 9 shows a correlation coefficient between the vehicle detectable distance and the normalized evaluation value D. From the result of FIG. 9, the correlation coefficient is 0.82 or more in the mark installed at the distance R up to 100 m, and the correlation coefficient is 0.9 or more in the mark installed especially within 80 m, which is a high value. If the size of the mark plate is 50 cm or more, or if the number of pixels in the mark plate region is about 10 pixels or more, a change in the environmental condition can be detected.

Reference data (1) -determined by the above method
(4) is stored (step T13) and set as reference data corresponding to the installation position of the mark plate. Alternatively, it may be stored as reference data for each of a plurality of mark plates, and may be selectively set (step T12) from the stored reference data according to the installation positions of the camera and the mark plate, or may be interpolated with respect to the distance. .

The normalized evaluation value output from the environmental condition detecting means 23 is collated with the reference data, and the obstacle detection capability is judged by a predetermined threshold value and output (step T11). The position of the sensor is determined based on the vehicle detection capability of the visible image sensor. The vehicle detection range is defined based on the vehicle detection capability of the sensor, that is, the technical condition that the presence or speed of the vehicle can be specified from the captured image by image processing. Based on the current visible image sensor performance, the vehicle detection range of the sensor can be adjusted by adjusting the camera angle.
In the curve section, the depression angle of the camera is deepened to improve the detection performance in the area close to the camera. The vertical direction vehicle detection range of the visible image sensor that monitors the curved section is 20 to 100 m.
Stipulated in the range of. Therefore, the detection range that the sensor must be able to detect is within 100 m and is determined by the arrangement interval at which the cameras are installed. For example, the detection range that the sensor must be able to detect is 20
When it is set to ˜80 m, the reference data shown in FIG. 7 is set.
That is, the normalized evaluation value D corresponding to the value of the vehicle detection distance 80m shown on the vertical axis of FIG. 7 is set as the predetermined threshold value Dref. The normalized evaluation value D that is output when the system actually operates or when the environmental condition deteriorates due to the occurrence of fog or the like is a predetermined threshold Dr.
When it falls below ef, it can be diagnosed that the obstacle detection performance has deteriorated. From the above, one side is 50 cm
By using the above mark plate or the mark plate in which the number of pixels in the mark plate area is about 10 pixels or more,
It is possible to diagnose deterioration of detection performance up to. Further, the height of the mark plate installed is preferably 3.8 m or more so that the mark plate is not blocked by a large vehicle.

Next, the obstacle detecting means 22 is the same means as the conventional image processing apparatus, and the obstacle is initially detected (step T).
4), tracking (step T5) is performed. Thereafter, the processing result output means 26 determines the processing result to be output (step T
6) Do. If a failure is detected by the device failure detection means 25 or the judgment of the self-diagnosis means 24 is less than or equal to a predetermined threshold value, the judgment result is taken as the processing result, and if not, the detection result of the obstacle detection means 22 is taken as the processing result. Is output (steps T6 and T14).

Device failure detection means 25 and self-diagnosis means 24
And the output by the obstacle means 22 is the information creating means 31.
Each output is processed by, and edited and classified and output. The data structure output by the information creating means 31 is shown in FIG.
It is shown in 0. The header portion 34 of the data structure is data common to the respective devices constituting the obstacle collision prevention support system such as the transmission source, the transmission destination, and the time. The data type of the data unit 35 by the obstacle information creating means is the type of the event that determines the detected event such as a stopped vehicle or a low-speed vehicle, the position of the obstacle,
The obstacle ID, oncoming vehicle ID, oncoming vehicle position, detection time, etc. are edited and output. Further, the data type by the device operation information creating means is edited and outputted as follows. 0: Normal (when there is no equipment failure and it is judged by the self-diagnosis means that the detection capability of the sensor does not decrease). 1: When a device failure is detected. 2: When self-diagnosis means determines that the detection capability of the sensor has deteriorated

The contents of information provided are determined by the obstacle information providing means for providing the driver of the passing vehicle with the obstacle information and the system operation notifying means for notifying the abnormal operation of the system based on the data output created by the editing and classification. Then, the information is output by the information board or the road-to-vehicle communication device. For example, when the data type by the device operation information creating means is 0, the obstacle information providing means uses the data of the obstacle information creating means to “stop 100 m ahead,” “low speed 100 m ahead”, “oppose”. Information such as "the vehicle is approaching" is determined and output. When the data type is 1, "service stopped" or the like, and when the data type is 2, "adjusting" or the like is determined and output by the system operation notifying means. By editing and classifying the output of the data type, it can be used as useful data as maintenance information at the time of device failure.

In this embodiment, by going through the above steps,
It is possible to automatically self-diagnose the deterioration of the detection performance of the visible image sensor due to a change in the environmental state due to the detection of a device failure, the occurrence of rain, fog, etc., and to notify the driver of the system operation status. In the present embodiment, the method of extracting the luminance as the observed value is shown as the method of obtaining the evaluation value of the environmental state detecting means 23, but the same procedure as that of the conventional visibility measuring device is used to calculate the average luminance value of black and white. Alternatively, the contrast of the mark plate may be obtained and used as the evaluation value. Further, in this embodiment, the environmental condition detecting means is shown by using the mark plate, but other target objects on the road, for example, white lines on the road may be used.

Further, in addition to the function of the obstacle collision prevention support system, by converting the evaluation value of the environmental condition detecting means into the visibility V and calculating it, the visibility information to the driver in advance as the environmental condition deterioration information in front. The functions provided as can be used together.

Embodiment 2 The schematic equipment layout, schematic configuration, and processing flow chart of this embodiment are the same as those of the first embodiment. The operation of the second embodiment will be described with reference to FIGS. FIG. 11 is a data diagram illustrating the normalized characteristic value D corresponding to the temporal change of the environmental state evaluation value when the environment such as fog changes suddenly.

In this embodiment, steps T1 to T11 are the same as in the first embodiment. The self-diagnosis means 24 compares the evaluation value output by the environmental state detection means with reference data,
When the determination result output T14 determines that the detection capability of the obstacle detecting means has deteriorated after the operations of steps T1 to T11 for determining the detection ability of the obstacle detecting means using the predetermined threshold value, the determination result is determined to be the same for one hour. Output as.

As for the normalized characteristic value D corresponding to the temporal change of the environmental condition such as fog, it is assumed that the environmental condition is suddenly changed due to fog flowing as shown in FIG. In such a case, even if it is determined that the detection capability of the obstacle detection means has deteriorated, the determination of deterioration of the detection capability and determination of cancellation of the reduction are repeated in a short time due to a sudden change in the environmental state. Even if the notification is given, the effect is weak, and the reliability of information provision may be impaired by increasing the annoyance. Therefore, when it is determined that the detection capability has deteriorated, the determination result is output as the same determination for a certain period of time in consideration of the passing time of the traveling vehicle.

In this embodiment, by going through the above steps,
It is possible to notify the driver of the abnormal operation state of the system as information on the safety side even if the environmental state repeatedly changes suddenly when it is determined that the detection capability is deteriorated.

Embodiment 3 The schematic arrangement of equipment of this embodiment is as shown in FIG. 12, and the dimension of one side provided on the rear surface of the camera 12 and the information plate 6 within 100 m of the field of view of the camera 12 is 50.
It is a mark plate of cm or more.

Schematic configuration of this embodiment, processing flow, and
The operation is similar to that of the first embodiment. The information board that provides the driver with information about the oncoming vehicle is preferably installed close to the start point of the curve so that the driver entering the curve section can obtain the latest information about the oncoming vehicle. It can be provided on the back of the plate and included within the field of view of the camera.

With the above-mentioned installation means, the mark plate can be constructed as a part of the information plate.

[0043]

As described above, according to the first aspect of the invention, the detection capability of the visible image sensor is automatically reduced due to the deterioration of the environmental condition due to the detection of equipment failure and the occurrence of rain, fog, etc. It is possible to self-diagnose and improve maintainability. Further, since the mark plate and the camera are commonly installed on the same pole and the visible image sensor itself is provided with the self-diagnosis means, the system configuration can be simplified.

According to the second aspect of the present invention, even if the environmental condition repeats sudden changes, it is possible to notify the driver of the abnormal operation state of the system as information on the safety side.

According to the third aspect of the invention, since the mark plate can be configured as a part of the information plate, it is not necessary to newly provide a pole for attaching the mark plate.

[Brief description of drawings]

FIG. 1 is a schematic device layout diagram of a first embodiment of the present invention.

FIG. 2 is a schematic configuration diagram of a first embodiment of the present invention.

FIG. 3 is a process flow diagram of the first embodiment of the present invention.

FIG. 4 is an explanatory diagram of a mark plate and a luminance distribution.

FIG. 5 is a diagram showing reference data (1).

FIG. 6 is a diagram showing reference data (2).

FIG. 7 is a diagram showing reference data (3).

FIG. 8 is a diagram showing reference data (4).

FIG. 9 is a diagram showing a correlation coefficient between evaluation values of reference data (1) to (4) and vehicle detection positions.

FIG. 10 is an explanatory diagram of a data structure output from the device operation information creating means and the obstacle information creating means.

FIG. 11 is a data diagram illustrating a normalized characteristic value D corresponding to a temporal change in an environmental state.

FIG. 12 is a schematic device layout diagram of a third embodiment of the present invention.

FIG. 13 is a configuration diagram of a conventional image processing apparatus.

FIG. 14 is a configuration diagram of a conventional visibility measuring device.

[Explanation of symbols]

Two poles 3 mark plate 4 Roadside processing equipment 5 beacon antenna 6 mark board 11 cameras 12 cameras 21 Input screen storage means 22 Environmental condition detection means 23 Self-diagnosis means 24 Equipment failure detection means 25 Processing result output means 31 Information creation means 32 Normal 33 In bad weather 34 Header 35 Data Division 41 Obstacle information providing means and system operation notifying means 50 Initial detection means 51 Tracking means 52 output means 100 curve section 101 Walls that block the line of sight 102 Stopped vehicle 103 oncoming vehicle 104 AHS vehicle 105 non-AHS vehicle 200 Brightness detector 201 image processing device 202 A / D converter 301 image memory 302 CPU 303 memory 304 output unit

Continuation of front page (56) Reference JP-A-11-53695 (JP, A) JP-A-63-188741 (JP, A) JP-A-8-219784 (JP, A) JP-A-11-41399 (JP , A) JP 5-89400 (JP, A) JP 10-320535 (JP, A) JP 2000-111644 (JP, A) JP 2000-90393 (JP, A) JP 2000-67368 (JP, A) Special Table 2000-505213 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) G08G 1/00-1/16 B60R 21/00 624 B60R 21/00 628

Claims (3)

(57) [Claims] 1. An obstacle detecting means comprising a camera installed on a roadside pole and an image processing device for detecting an obstacle such as a stopped vehicle or a low speed vehicle existing in a curved section by using an image captured by the camera, Obstacle information creating means including an information processing device that creates provided information based on the output of the obstacle detecting means, an information version installed on the roadside, or obstacle information to a driver of a passing vehicle by a road-to-vehicle communication device. In an obstacle collision prevention support system having an obstacle information providing means for providing, an equipment failure detecting means for detecting a failure of a camera or the like, and an environmental condition detecting means for detecting an environmental condition such as rain, fog, etc. And a self-diagnosis means for self-diagnosing and outputting the detection capability of the obstacle detection means from the output of the environmental state detection means, and the operation of the equipment based on the outputs of the self-diagnosis means and the equipment failure detection means. An obstacle collision prevention support system, comprising: device operation information creating means for creating status information; and system operation notifying means for notifying a driver of an operating status of the system. Among the cameras, a mark plate with a side of 50 cm or more provided on a pole to which at least one camera is attached, and both the mark plate and an obstacle on the road are photographed by including the mark plate within a field of view of 100 m or less. The change in environmental condition is detected by extracting the brightness of the mark area from the image of the camera that captures the mark plate and the evaluation value by normalizing with the evaluation value obtained in the past and fine weather. In the past, the self-diagnosis means installs a mark plate at a position in front of the camera in front of the camera, and detects an environmental condition by detecting an environmental state and an obstacle detecting means. Further, in the past, a means for storing and setting reference data consisting of an evaluation value of the environmental condition detected for each change of the environmental condition and a vehicle position detection result in the past is provided, and the evaluation value output by the environmental condition detecting means is used as the reference data. Equipped with a self-diagnosis unit that collates and determines a decrease in the detection capability of the obstacle detection unit based on a predetermined threshold value and outputs it. The device operation information creation unit edits and outputs the output from the device failure detection unit and the self-diagnosis unit. An obstacle collision prevention support system characterized in that 2. The self-diagnosis means collates the evaluation value output from the environmental condition detection means with reference data, and judges the deterioration of the detection capability of the obstacle detection means by a predetermined threshold value, the judgment result is determined to be the same for a certain period of time. The obstacle collision prevention support system according to claim 1, wherein 3. A mark plate is provided on the back surface of the information plate,
2. The obstacle collision prevention support system according to claim 1, further comprising an environmental condition detecting means including a camera that captures an image of both the mark plate and an obstacle on the road within a field of view of 0 m or less.